Multispectral remote sensing for determining dry severity levels of pointers in eucalyptus spp.

Abstract

The objective of this work was to develop a methodology for the processing and analysis of images obtained by the multispectral sensor in a UAV (Unmanned Aerial Vehicle) to assist in the characterization of the spectral response of Eucalyptus urophylla x E. grandis with an occurence of dry pointers caused by the bacterium Erwinia psidii. The methodology consisted of three main steps: Obtaining the digital images through RPA flights, equipped with multispectral camera; characterization of disease levels in a plot of field monitoring, and; digital processing of the images to obtain eleven vegetation indexes, compared at different levels of severity, and evaluated using statistical tests: Shapiro-Wilk, Levene, ANOVA, Kruskal-Wallis and Wilcoxon. These indicated that the Plant Senescence Reflectance Index (PSRI) is the most adequate to differentiate the severity levels of the disease. The healthy area of the field represented 30.38% of the study area, 17.48% is represented by planting lines and exposed soil, while the area with some level of disease severity corresponded to 52.14%.